• 제목/요약/키워드: Genetic Programing

검색결과 15건 처리시간 0.014초

풍속 예측 보정을 위한 Genetic Programing 탐색 기법의 개선 (Improvement of Search Method of Genetic Programing for Wind Prediction MOS)

  • 오승철;서기성
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2015년도 제46회 하계학술대회
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    • pp.1349-1350
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    • 2015
  • 풍속은 다른 기상요소들보다 순간 변동이 심하고 국지성이 강하여 수치 예보 모델만으로 예측의 정확성을 높이기가 어렵다. 기상청의 단기 풍속 예보는 전 지구적 통합 예보모델인 UM(Unified Model)의 예측값에 MOS(Model Output Statictics)를 통한 보정을 수행하며, 보정식의 생성에 다중선형회귀분석 방법을 사용한다. 본 연구자는 유전프로그래밍(Genetic Programming)을 이용한 비선형 회귀분석 기반의 보정식 생성을 통하여 이를 개선한 바 있는데, 본 연구에서는 보다 향상된 성능을 얻기 위하여 GP 기법 측면에서 Automatically Defined Functions과 다군집(Multiple Populations) 수행을 통해 성능을 높이고자 한다.

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장비 수율을 고려한 가공경로선정과 투입량 결정에서의 유전알고리즘 접근 (Machining Route Selection and Determination of Input Quantity with Yield Using Genetic Algorithm)

  • 이규용
    • 한국산업경영시스템학회:학술대회논문집
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    • 한국산업경영시스템학회 2002년도 춘계학술대회
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    • pp.99-104
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    • 2002
  • This paper addresses a problem of machining route selection and determination of input quantity with yield in multi-stage flexible flow system. The problem is formulated as nonlinear programing and the proposed model is solved by genetic algorithm(GA) approach. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound for the same problem.

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System의 수행도를 개선시키기 위한 유전자 알고리즘의 도입에 관한 연구 (A Study on the Introduction of Genetic Algorithms for Developments Performance of System)

  • 김병석;김용범;장병집
    • 한국안전학회지
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    • 제13권4호
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    • pp.240-247
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    • 1998
  • This paper proposed a method for solving the nonlinear integer programing problem to get easily the best compromise solution while holding a nonlinear property by using the genetic algorithms. Also, this paper reported that the optimization problem of systems reliability as was solved by using the preposed method, and the numerical comparison experiments between the 0-1 LP/0-1 NP formulations were demonstrated, and from the quantitative evaluation the efficiency of the proposed method was demonstrated.

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순차적으로 선택된 특성과 유전 프로그래밍을 이용한 결정나무 (A Decision Tree Induction using Genetic Programming with Sequentially Selected Features)

  • 김효중;박종선
    • 경영과학
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    • 제23권1호
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    • pp.63-74
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    • 2006
  • Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

유전적 프로그래밍을 이용한 응답면의 모델링 II: 최적의 다항식 생성 (Response Surface Modeling by Genetic Programming II: Search for Optimal Polynomials)

  • 이욱;김남준
    • 정보기술응용연구
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    • 제3권3호
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    • pp.25-40
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    • 2001
  • 본 논문에서는 유전적 프로그래밍(Genetic Programing)을 이용하여 최적의 다항식을 생성하는 기법을 제시하고자 한다. 다항식은 비선형성이 큰 응답면을 모델링해야 하며, 이를 위하여 GP 트리 생성시 2-3차 오더의 Taylor Series를 사용하는 방법을 시도하였다. 아울러 생서되는 다항식의 크기를 제어하기 위해서 GP 트리가 표현할 수 있는 다항식의 최대 차수를 제한함과 동시에 하나의 주 트리와 보 트리로 구성되는 GAGPT(Group of Additive Genetic Programming Trees) 사용을 모색하였다. 마지막으로 두 개의 응용 예를 통하여 본 방법의 유용성을 검증하였다.

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유전 알고리듬을 이용한 연속 공정의 최적 제어 (Optimal control of continuous system using genetic algorithms)

  • 이무호;한종훈;장근수
    • 제어로봇시스템학회논문지
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    • 제3권1호
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    • pp.46-51
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    • 1997
  • The optimal control of a continuous process has been performed using genetic algorithms(GAs). GAs are robust and easily applicable for complex and highly nonlinear problems. We introduce the heuristics 'dynamic range' which reduces the search space dramaticaly keeping the robust search of GAs. GAs with dynamic range show the better performance than SQP(Successive Quadratic Programing) method which converges to a local minimum. The proposed methology has been applied to the optimal control of the continuous MMA-VA copolymerization reactor for the production of the desired molecular wieght and the composition of VA in dead copolymer.

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다단계 작업장에서의 가공경로 선정과 투입량 결정 (Machining Route Selection and Determination of Input Quantity on Multi-Stage Flexible Flow Systems)

  • 이규용;서준용;문치웅
    • 산업경영시스템학회지
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    • 제27권1호
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    • pp.64-73
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    • 2004
  • This paper addresses a problem of machining determination of input quantity in a multi-stage flexible flow system with non-identical parallel machines considers a subcontracting, machining restraint, and machine yield. We develop a nonlinear programing with the objective of minimizing the sum of in-house processing cost and subcontracting cost. To solve this model, we introduce a single-processor parallel genetic algorithm(SPGA) to improve a weak point for the declined robustness of simple algorithm(SGA). The efficiency of the SPGA is examined in comparison with the SGA for the same problem. In of examination the SPGA is to provide the excellent solution than the solution of the SGA.

뱀형 로봇의 모델링과 진화연산 기반 이동 생성 (Modeling of Snake-like Robot and Evolutionary Computation based Generation of Locomotion)

  • 서기성;장재영;안인석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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    • pp.121-123
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    • 2009
  • 뱀형 모듈라 로봇은 다양한 환경에 대해서 강인성을 가지고 있고, 모듈 일부의 고장에도 이동할 수 있는 장점을 가진다. 그러나 이동 제어 방법이 어렵고, 아직까지 효율적인 이동법의 개발이 미비한 편이다. 본 연구에서는 뱀형 로봇의 이동제어를 위하여 GA(Genetic Algorithm)기반의 위상제어 방식과 GP(Genetic Programing)를 사용한 임의의 관절궤적 생성 방식을 비교한다. KMC사의 뱀형 로봇을 대상으로 먼저 webots 시뮬레이터 상에서 모델링 및 시뮬레이션을 수행하여 위의 방법들을 비교하였다.

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패턴 인식을 위한 진화 셀룰라 분류기 (Evolvable Cellular Classifiers for Pattern Recognition)

  • Ju, Jae-ho;Shin, Yoon-cheol;Hoon Kang
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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    • pp.236-240
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    • 2000
  • A cellular automaton is well-known for self-organizing and dynamic behaviors in the field of artificial life. This paper addresses a new neuronic architecture called an evolvable cellular classifier which evolves with the genetic rules (chromosomes) in the non-uniform cellular automata. An evolvable cellular classifier is primarily based on cellular programing, but its mechanism is simpler because it utilizes only mutations for the main genetic operators and resembles the Hopfield network. Therefore, the desirable hi t-patterns could be obtained through evolutionary processes for just one individual agent. As a result, an evolvable hardware is derived which is applicable to classification of bit-string information.

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작업장 특성을 고려한 가공경로선정 문제의 유전알고리즘 접근 (-Machining Route Selection with the Shop Flow Information Using Genetic Algorithm-)

  • 이규용;문치웅;김재균
    • 산업경영시스템학회지
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    • 제23권54호
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    • pp.13-26
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    • 2000
  • Machining route selection to produce parts should be based on shop flow information because of input data at scheduling tasks and is one of the main problem in process planning. This paper addresses the problem of machining route selection in multi-stage process with machine group included a similar function. The model proposed is formulated as 0-1 integer programing considering the relation of parts and machine table size, avaliable time of each machine for planning period, and delivery date. The objective of the model is to minimize the sum of processing, transportation, and setup time for all parts. Genetic algorithm approach is developed to solve this model. The efficiency of the approach is examined in comparison with the method of branch and bound technique for the same problem. Also, this paper is to solve large problem scale and provide it if the multiple machining routes are existed an optimal solution.

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